After more than five years of development behind the curtain, the time has
come to release a new version of aubio.

The list of changes is long, but to make it short, aubio is now:

more portable: with no required dependencies, the core of aubio
library, written in ANSI C, is known to compile and run on most modern
platforms (Linux, Windows, Mac OS X, Android, iOS, ...).

more stable: several bugs fixes and a battery of tests make this new
release more robust and less prone to errors.

faster: several enhancements to the C library and a brand new Python interface help make this release orders of
magnitude faster than the previous ones.

Several new features have been added, including:

the new source object uses libav to read audio samples from any audio or video
file, compressed or uncompressed, including over different network protocol.
(On Apple systems, decoding of most audio formats is also possible using CoreAudio).

a new filterbank object, completely
customizable, allows for computing energies in any number of custom designed
spectral bands.

a new mfcc object computes the Mel
Frequency Cepstrum Coefficients (MFCC). It is implemented according to Malcom
Slaney's Auditory
Toolbox.

new spectral descriptors, including
statistics such as centroid, skewness, slope, decrease, rolloff, and kurtosis.

An audio example is worth a thousand characters. Here are a few examples of
graphs obtained using the new Python interface.

Examples of plots obtained using aubio's new Python interface. From top to
bottom, left to right: a. Onset detection on recording of an electric bass
guitar with distortion. The original waveform is shown in the upper part, while
the lower part shows the onset detection function (green), the thresholded
function (yellow), and the detected onsets (red) (source
code). b. Pitch detection on a male voice. The middle plot shows the
detected f0 (dashed green) and the detections for which the confidence is
higher than a given threshold (blue). The bottom plot shows the confidence for
each frame (blue) and the confidence threshold (green) (source
code). c. Energies found in 40 bands equally spaced on the Mel scale,
obtained on a sample containing a guitar and a keyboard (source
code). d. Different spectral descriptors computed on a drum loop, showing
the behavior of these functions for different percussive sounds (source
code).